مرتضی بیطرف ثانی

Camel breeding is one of the sources of income for people on the edge of arid and desert areas in many parts of the world. Traits related to camel growth, including birth weight, weaning weight, daily weight gain and one-year-old weight are considered as the main economic traits for camel owners. To manage and improve the genetic and phenotypic values of these traits, weight recording of animals is essential. Recording of camels, especially their weight is associated with many difficulties due to their restless temperament and large size. Using efficient mathematical methods can greatly solve this problem. Various approved efficient mathematical methods have been proposed to predict the weight of camels based on their body dimension, and their effectiveness has been proven. So, the present study was conducted to compare the efficiency of the Principal Component Analysis and multiple regressions in estimating the weight of fattening camels from its body dimensions.

In order to compare the efficiency of principal components analysis and multiple regressions in estimating the weight of fattening camels based on body dimensions, the records of 220 fattening camels of Bafgh station in Yazd were used. For this purpose, new born camels were fed for a 9 months period using standard diets. During the period, each of the fattening camels was weighed and different body sizes including body length(BL), whither height(WH), breast girth(BG), abdomen with(AW), hump height to the ground(HH), muzzle girth(MG), neck length(NEL), whither to pin length(WPL), tail length(TL), pelvic width (PW), abdomen to hump height (ABH) and the head length(HL) were measured. The body dimensions of the camels were recorded using a tape measure and their body weight was recorded using a scale. Then, the data were analyzed using the principal component analysis and multiple regressions. In order to fit the predictive models, body weight of camels was introduced as dependent variable and body size of camels as independent variables. Analysis of regression models was done using one and multivariable linear models and the best model were selected to estimate the weight of camels based on their body dimensions by Stepwise method. The performance of the above models was evaluated using comparison of the coefficient of determination (R2) of them.

According to the results, the correlation between the body weight of camels with their different body dimensions including BL, WH, BG, AW, HH, MG, NEL, WPL, TL, PW,ABH and HL were 0.93, 0.89, 0.89, 0.89, 0.94, 0.73, 0.89, 0.90, 0.80, 0.85, 0.89 and 0.79 ,respectively. The results showed that among the 6 multiple regression models fitted to estimate the weight of fattening camels, model No. 6 in which head length, body length, breast girth, neck length, muzzle girth and whither height were used as predictive variables had the least error (12.06) and the highest accuracy (0.92) compared to other models. The results showed that the use of the first and second principal component , and both of them in the model could explain 82.1%, 3.73% and 85% of the variance of body weight, respectively. The weight of fattening camels was determined using principal component analysis with an accuracy of 0.93 and an error of 11.54.

The results of the present study showed that in order to estimate the weight of fattening camels, the use of principal component analysis, in addition to simplifying predictive models, has higher efficiency and accuracy as well as less error compared to multiple regressions, and this method can be a suitable alternative to the multiple regression method in predicting the weight of camels.

Sistani cows are generally restless animals; therefore, controlling, treating, and weighing them is difficult. On the other hand, recording the weight of domestic animals, including Sistani cows, is inevitable, because it provides a good scale for management decisions in the herd such as balancing the diet, changing environmental conditions, or determining the time of slaughter of fattening animals. In addition to scales, various methods are commonly used to measure the body weight of large animals. Some of these methods include the use of weight-meters, appraisal assessments, and the use of mathematical models. One of the new methods for predicting livestock weight is artificial intelligence. Because some reports are indicating that artificial intelligence could facilitate the weighing process of animals, this study was performed to predict the body weight of Sistani cows using computer vision technology. The data required for this study were recorded in the Zahak breeding station located in Sistan and Baluchestan province of Iran. The recording operation involved the weighing and biometric measurement of about 190 Sistani cattle, including calves, heifers, and male and female animals, every three months during a year. At the time of weighing, images of the lateral view of each animal were taken and recorded using the CANON SX150IS digital camera. During this period, a total of 358 weight records of Sistani cows at different ages were recorded. The digital images were initially preprocessed using MATLAB software, and then some morphological features were extracted from each image. For predicting the weight of Sistani cows via the Artificial Neural Network (ANN), the extracted features of images were introduced to the ANN model as input and the weight of cows as output. The "feed-forward neural network", which was trained by the "error propagation" algorithm, was used to predict the weight of cows. The function used in the hidden layer of the ANN model was sigmoidal and in the output layer was linear. An ANN model which had the highest precision and lowest error was selected as the final model for predicting the animal weights. The criteria for selecting the best model were the highest determination coefficient (R2) and the lowest mean square error (MSE) compared to other available models. Out of 22 features extracted from each image, only 15 of them, which had a higher correlation with the body weight of cows at different ages, were selected as effective features. As result, equivalent diameter, major axis length, minor axis length, bounding box, convex area, filled area, area, perimeter, and the number of non-zero pixels of the image (NNZ) had the highest correlation with the cattle weights (P<0.01) and used as effective features to train the ANN model. The final ANN model had 15 neurons in the input layer including selected image features, 11 neurons in the hidden layer, and one neuron in the output layer including the weight of the cows. The precisions of the artificial neural network in the training, validation, and test phase were 0.974, 0.970, and 0.981, respectively. The results showed that the final ANN model had acceptable precision in all light, medium, and heavy-weight cows, and the size and the age of animals did not have a significant effect on the precision of the artificial neural network model. A correlation between the actual weight of Sistani cows and the weights predicted by the ANN model was 98.3%. The average error of the model in predicting the weight of cows was 1.11%. In the practical test, a 2.32 kg deviation was observed between the predictions of the ANN model and actual weights in Sistani cows. The accuracy of the ANN model for predicting the weight of Sistani cows in the present study is acceptable and within the range of the other reports. The proposed method based on image processing and ANN, had acceptable results in predicting the weight of Sistani cows. Given the difficulties of weighing Sistani cows as heavy livestock and sometimes the time-consuming process, it seems that the use of new technologies such as computer vision methods can be a good alternative to conventional weighing methods and facilitate and reduce recording costs of Sistani cows.

In order to identify, register, certify, control and protect the country's livestock and poultry genetic reserves, a comprehensive system should be designed, which consists of the sub-sections like “preparing a comprehensive atlas”, “distribution map”, “accurate statistics and monitoring of the existing populations of the country's indigenous livestock and poultry genetic reserves”. . Therefore, this study has been conducted to introduce the population and breeds of livestock and poultry of the country aiming at designing of the "Atlas of genetic resources of livestock and poultry of the country" application program. In this application, the users can easily get to know the livestock and poultry breeds of each geographical region and observe their breed and breeding characteristics. Also, this app has a user-friendly search feature. The information can be updated from the application panel. In this application, there is a section called "Registration of new species" that can be obtained from the population and breeds of livestock and poultry all over the country with the voluntary participation of people. This information will be used in the database after filtering on the management panel.

Using efficient mathematical methods can be effective in order to breed identification and genetic grouping. So, the aim of this study was to compare the morphological features of native camels of central desert of Iran with dairy camels of Pakistan using the principal component analysis method. For this purpose, 25 native camels of Iran and 62 dairy camels of Pakistan were used. Measurements of shoulder height, pin width, udder circumference and udder depth were considered. Principal component analysis (PCA) carried out using ggfortify package in R version 3.5.3. Also, scores of camel type were compared using the independent samples t-test in SPSS software (version 22). The results showed that Pakistan’s dairy camels was taller than native camels (p <0.05). Pin width, udder depth, and udder circumference in Pakistan’s camels were larger than native Iranian camels (p <0.05). The mean evaluation score of Iranian native camels was 57.12 ± 10.03 and in camels of Pakistani origin was 76.71 ± 12.31 (p <0.05). The results of PCA showed that native camels of the central desert of Iran and dairy camels of Pakistan are in two separate categories and have different morphologies. The results of the present study showed that it is possible to use mathematical methods including principal component analysis (PCA) in order to accurately distinguish Iranian native camels from dairy camels of Pakistan origin.

The present study aimed to determine the best mathematical model to describe the growth curve of dromedary camels. For this purpose, the data recorded between 1990 and 2018 in the National Research and Development Station on Dromedary Camel located in Bafgh, Yazd province, were used. The records included the body weight of 747 dromedary camels at different ages (from birth to 14 months of age). To determine the best model describing the growth curve of dromedary camels, eight different mathematical models including linear, quadratic, cubic, Gompertz, Brody, logistic, monomolecular, and von Bertalanfy were compared. The age of camels was included in the model as an independent variable and the weight of camels as a dependent variable. The criteria for comparing the performance of the models were having the highest value of the corrected coefficient of determination (R2 adj) or the lowest values of Akaike information criterion (AIC) and the mean square error (MSE). Based on the results of this study, the accuracy of linear, quadratic, and cubic equations in describing the growth curve of dromedary camels was significantly lower than that of Gompertz, logistic, monomolecular, von Bertalanfy and Brody models. The results of the present study showed that the weight of dromedary camels could be predicted precisely up to weaning age (200 days), However, after weaning, due to the effect of different environmental conditions on the growth of camels and a sudden change in feed type, the increase in camel weight does not have a linear relationship with their age, and it is better to use other parameters such as biometric measurements to accurately estimate camel weight.

Environmental pollution by cadmium (Cd) is increasing. The entry of this heavy toxic metal into the food chain is a serious danger to human and animal populations. This study aims to evaluate the effect of turmeric (Curcuma longa) powder (TP) containing 2.96% of total curcuminoides (TCM) in modulating the adverse impacts of Cd in Japanese quail. 180 22-day-old male Japanese quails were randomly divided into six groups for 23 days and fed a basal diet (BD) supplemented with 3 gr/kg TP (containing 88.18 mg of TCM), 5 mg/kg TP (containing 148 mg of TCM), 100 mg/kg Cd, 3 mg/kg TP plus 100 mg/kg Cd, and 5 gr/kg TP and 100 mg/kg Cd. The addition of TP to the Cd-contaminated diet reduced serum levels of pro-inflammatory cytokines TNF-αand IL-6, improved total antioxidant capacity, increased SOD and CAT activity, as well as decreasing MDA concentration. The TP supplementation significantly (p<0.05) reduced the harmful effects of Cd on body weight loss, relative liver weight gain, and total protein concentration, besides increasing serum levels of ALT, AST, and ALP enzymes. The findings of this study suggest that TP may reduce the toxic effects of Cd in Japanese quail by improving antioxidant status and reducing the activity of pro-inflammatory cytokines. The addition of 5 g/kg TP to the Cd-contaminated diet results in more antioxidant and anti-inflammatory properties than 3 g/kg TP.

One of the major challenges in camel husbandry is the lack of records and registration. The camel breeding system in the country is Extensive and dependent on rangelands and the long distances and high dispersal of herds have added to the problems of recording and the establishment of net. On the other hand, recording, especially in weights of camels, is very difficult and it is necessary to use statistical models and estimation of body weight by body measurements. Networking to communicate camel breeders with each other and education and research centers can provide camel productivity in the country. therefore, it is necessary to use ICT in camel husbandry. In camel breeder assisted system, by communicating through the SARBANYAR app, in addition to communicating and providing skill training, camel breeder knowledge in the mobile platform will be enhanced. The camel herd is also tracked online using the GPS hardware and this APP.

Body size is one of the main features for the classification of horses. Among these features, the length of the body is one of the aspects that considered essential for animal's nutrition and height at withers applies for intra-species separating. Genome Wide Association Studies have demonstrated LCORL gene code a transcription factor that those polymorphisms are associated with skeletal frame size and body length. Recently, BIEC2-808543 SNP located upstream of LCORL was identified as a genetic diagnostic marker associated with withers height and also the length of Cannon bone in Thoroughbred horses. BIEC2-808543 is This SNP effect on TFIID binding site in TATA box. The substitution of C to T allele causes changes affinity of TFIID to TATA box. because of this is the effect on indicating TFIID by a pro-motor nuclear element which is the first step in mRNA transcription and in result effects on other transcription factors of bone-like AP-1, activator protein-1 transcription factor complex, AP-1 is activated as one complex of mRNA and subsequently transcription get higher. On the other words, skeletal bones are expanded by three chondrocytes, osteoblasts and osteoclasts cells. The difference and performances of these cells are regulated by some special factors that are effective on gene expression.
Near the LCORL gene in chromosome 3, there is a QTL which is associated with height at withers, composition of legs, length of horse' s rump, head and jaw of the horse. The purpose of this research was studying of genotype and allele frequency of BIEC2-808543 and its relationship with body size in Iranian Arab horse.

A total of 152 (85 males and 67 females) Iranian Arab horses were used in this study. All horses were born between 1990–2015, and the mean of age was 7.3 years. All horse's data were registered at WAHO and was get from Yazd Arabic Horseshoe. The time of this research was 1396 and the information was gathered from horse breeding clubs in the city of Ashkezar. The city of Ashkezar is the center of Arabic horse breeding. Measurements included withers height (cm), chest circumference (cm), and leg length. Also, each horse was judged as view of foot, head and neck and score of 0-20 was registered. The referee of this research was experienced experts in the Iranian horses' club located in Yazd. Blood samples were collected from 141 animals and in the molecular genetic laboratory of Islamic Azad University of Ashkezar stored at −20°C. Genomic DNA was extracted by Gene All kit (Company Gene All, South Korea (according to the manufacturer’s protocol. We used Thermocycler for PCR and duplication fragments. The volume of the reaction was 25 μl including 14 μl master mix, 1 μl forward, 1 μl reverse, 9μl water. Genotyping for BIEC2-808543 was performed using by PCR-RFLP by Alu1 (Company Sina Clone) restriction enzyme. primer designing was applied primer 3 software and the Restriction Mapper software (Online site was used) for PCR was used to distinct the used restriction enzyme. Forward primer sequence has TGGAGTCAGTTGGGTTTAATG and Reverse primer sequence has GACCGGATAGCATAGAGAGAG. Genetic association analysis for withers height, chest circumference, leg length, and judgment scores were performed using SNPassoc package (R software). compare mean between race and show horse was performed using Non-parametric mann-whitneyU. Weir&Cocker ham'sFst was estimated by FSTAT software.

Results of Genotyping of BIEC2-808543 SNP showed that one of the horses with the name of Meraj Mofidian (father name: Zelzeleh) is CT. The others were TT genotype. In this study 99/2% of horses had the TT genotype. Results represent fixation of T allele of BIEC2-808543 SNP on this gene in Iranian Arab horses. There was no significant difference between scores in three aspects, hands, legs, head and neck of show and race horses. Also, Genotype frequency of BIEC2-80543 SNP of show and race horse was similar. Estimated FST between race and show horses was tiny amount (-0.005) and show no genetic difference of LCORL gene between two groups. Though there was no significant difference of withers height, and leg length and judgment scores between race and show groups.

Allele T in BIEC2-808543 polymorphism in Iranian Arab horse stabilization and approves endurance of this breed. Race Iranian Arab horse have bigger Chest circumference because of racing in short distances.

The evolution of single and two humped camels dating back to 40 to 45 million years ago, when the Camelida family was evolved during the Eocene in North America. Genus Camelini and Genus Lamini, which includes species of Guanaco, Lama, Alpaca, and Vicugna, were evolved from the Camelida family, about 11 to 25 million years ago. Old world camel can be divided into wild and domestic one and two humped camels, in which wild type of one humped camel has been distanced centuries ago (Burger 2016). Among 150,000 of Iranian one-humped camel, there are about 2,000 one-humped (Turkmen) camels, which are the country’s major species (Ansari Renani et al 2010), whom mainly rearing in Golestan province. Single-humped camels are used mainly for the purpose of producing meat, milk, transport, hair, and sports (Abdel-Aziem et al. 2015; Ramadan and Inoue-Murayama 2017). Several studies in different species have shown that the genetic polymorphisms of the Myostatin gene can increase the lean meat (Mosher et al. 2007). The identified polymorphisms of the gene in the camel included mutations in non-coding regions and synonymous mutations in coding regions (Shah et al. 2006; Sajadi Zirjani et al. 2016). Myostatin or Growth differentiation factor 8 (GDF8) is a member of beta-transforming family (TGF-β) that limits muscle mass (Wang and Mcpherron 2012). The mutation in the Myostatin gene increases muscle mass through the growth and proliferation of its cells (Mosher et al. 2007). The Myostatin gene with its three exons and two introns, has been sequenced in wild and domestic two-humped and domestic Arabian camel. The aim of this study was to investigate the sequence of the Myostatin gene (Gene ID: 105099167) of Camellus Bactrianus, Ferus, Dromedarius (Arabian) and some other species with Iranian Turkmen Dromedarius camel. Therefore, the evolutionary relationships among different species in terms of the sequence of this gene can be determined using phylogenetic study. For this reason, the whole genome sequence of Turkmen camel was performed and Myostatin gene sequences of different species were obtained from data banks.

The blood sample was obtained using syringe from the abdominal vein of a pure Iranian Turkmen camel, then stored in an EDTA containing plastic tube. After extraction, one microliter of the product was used to measure concentration using QubitTM Fluorometer (Invitrogen, Cat. No. Q32857). After evaluation, the sample was sent for whole genome sequencing using the Illumina HiSeq 2000 platform. After trimming the results, reads were assembled and the reads containing the Myostatin gene were extracted from the whole data set. To compare the different species of camels, the Myostatin gene sequence of Arabic camels, wild Bactrian camel, domesticated Bactrian camel, and Alpaca were obtained from NCBI. Using the CLC Genomics Workbench 12 software, alignment was performed to compare and obtain the sequences of the Myostatin gene in old and new world camels. Alignment for comparison of Myostatin gene sequence parameters of different camel species were conducted using CLC Genomics Workbench 12 software. Then, the number of gaps, differences, distances, identity percent, and identity of Myostatin gene sequence nucleotides was considered in different camel species. To study the degree and the relative time of divergence of the camel species, a phylogeny tree using neighbor-joining method was prepared. Also, annotation information of Myostatin was used to extract exons and introns of the gene. Then, the number of gaps, differences, distances, identity percent, and identity of Myostatin protein sequences was considered in different camel species. The phylogenetic and evolutionary situation of the Turkmen camel compared to many other species.

Concentration of extraction product was 304 ng/μl. A total of 589,326,158 clean reads of about 88 billion nucleotides in paired end mode with the length of 150 base pairs were obtained. The Myostatin gene sequence was extracted from the assembled whole data set. Alignment results of Myostatin gene sequence in different camel species showed the greatest gap, differences and distance, and the least similarity between the alpaca species and other camel species were obtained. Also, the most similarity obtained between wild and domestic two-humped camels. The phylogenetic tree obtained from the gene sequence alignment revealed that Alpaca is far apart from other camel species. Among old world camels, the two-humped camels are more distinct from the Arabian one-humped camel. The length of the exons in different species was equal, but not the sequence, and exon alignment showed evolutionary conservation of exon length and ultimately the protein length. Considering identity and differences of exons and gene sequence revealed that Alpaca is more distant from other species. Also, one-humped and two-humped camels were similar to each other. The results are consistent with the results of Shah et al. (2006), which did not observe any polymorphism by sequencing of exon 1 of this gene. In the study of Yi et al. (2017), domestic and wild two-humped camel were located in different branches of the phylogenetic tree. In this study, the Iranian Turkmen camel was located in a separate branch between the two-headed and one-humped Arab camels. Myostatin gene alignment was conducted between different species and the phylogenetic tree showed that camels, horses, sheep, goats and cows belong to different groups. In the study of Hedayat-Evrigh et al. (2016), it was found that one-humped and two-humped camels were far away from cattle and horses. Homology between sheep and goat, as well as przewalski horse and the horse were complete. The lowest homology of 92.82 was found between humans and buffaloes. The greatest gaps of 3236 nucleotide were seen between sheep and donkeys.

Although there are differences between the nucleotide sequence of the introns and the exons of Camelida family, there was no difference in amino acid sequence of the gene, which indicates the strong protection of this gene during the evolutionary period. It can be said that numerous mutations in the gene have been eliminated during natural selection and no evolutionary opportunity has been provided for the mutations. The study of the homology and difference between the 16 species revealed that the homology of the protein sequence is very high in different species.

Decision tree is the data mining tools to collect, accurate prediction and sift information from massive amounts of data that are used widely in the field of computational biology and bioinformatics. In bioinformatics can be predict on diseases, including breast cancer. The use of genomic data including single nucleotide polymorphisms is a very important factor in predicting the risk of diseases. The number of seven important SNP among hundreds of thousands genetic markers were identified as factors associated with breast cancer. The objective of this study is to evaluate the training data on decision tree predictor error of the risk of breast cancer by using single nucleotide polymorphism genotype.
The risk of breast cancer were calculated associated with the use of SNP formula:xj = fo * In human, The decision tree can be used To predict the probability of disease using single nucleotide polymorphisms .Seven SNP with different odds ratio associated with breast cancer considered and coding and design of decision tree model, C4.5, by Csharp2013 programming language were done. In the decision tree created with the coding, the four important associated SNP was considered. The decision tree error in two case of coding and using WEKA were assessment and percentage of decision tree accuracy in prediction of breast cancer were calculated. The number of trained samples was obtained with systematic sampling. With coding, two scenarios as well as software WEKA, three scenarios with different sets of data and the number of different learning and testing, were evaluated.
In both scenarios of coding, by increasing the training percentage from 66/66 to 86/42, the error reduced from 55/56 to 9/09. Also by running of WEKA on three scenarios with different sets of data, the number of different education, and different tests by increasing records number from 81 to 2187, the error rate decreased from 48/15 to 13/46. Also in the majority of scenarios, prevalence of the disease, had no effect on errors in the WEKA and code.
The results suggest that with increased training, and thus the accuracy of prediction error decision tree to reduce the risk of breast cancer increases with the use of decision trees. In Biological data, decision trees error is high even with a 66/66% training. On the other hand by increasing the number of SNP from 4 to 7 decision tree, decision tree error dramatically decreased at 70/1% training. In general we can say that with increased training and increasing the number of SNP in the decision tree, the prediction accuracy increased and errors reduced. In the CODING and WEKA, percentage of disease prevalence had no significant effect on errors,” Because of selecting set of training and testing by systemic method “.

Age at first calving (AFC) has an important effect on profitability and reproductive management of dairy cattle. Every month increase in AFC beyond 24 months increases the cost of production. The time between birth and first calving represents a period in which replacement heifers are not generating income. Instead this rearing period requires considerable capital expenditures including feed, housing, and veterinary expenses. These expenses constitute 15% to 20% of the total expenses related to milk production. A basic approach to reduce this cost is to decrease the time between birth and her first freshening. Worldwide recommendations for one particular AFC might be an incorrect management goal for all of the cattle on all of the farms, since the recommendation might not represent the management goals and/or capabilities of a particular production system or farm. We realize that each dairy has its own set of unique management and environmental conditions, which makes a universal AFC and BW after first calving, a difficult goal to achieve. The AFC has a profound influence on the total cost of raising dairy replacements in which older calving heifers are more expensive to raise than younger ones. A total of 19499 calving records belonged to 96 herd from 1996 to 2008 were used to estimate genetic components and genetic trend for age at first calving in Holstein dairy cows of Iran. Data were analyzed using a univariate model and Wombat software. Linear regression of estimated breeding values on calving year was used to estimate genetic trend. Estimated genetic trend was positive for some years and was negative for others and showed that reducing age at first calving has not been considered in the selection strategies; however, the phenotypic trend was decreased. The age at first calving for Yazd, Markazi, and southern Khorasan provinces were the highest and for Kermanshah, East Azarbayjan, and Ardebil provinces were the lowest compared to the other provinces. Most analysis shows that the financial benefit afforded to heifers that freshen at a low AFC seems to at the least offset any milk lost in the first lactation. The NRC (2001) suggests a post weaning BW equal to 82% of her mature body weight. This can be attained with a maximal pre-pubertal ADG of 2.0 lbs/d if a traditional pre-weaning program is employed or 1.8 lbs/d if an intensified pre-weaning program is employed. Due to the well-defined link between insufficient BW at calving and increased mortality and disease in first calf heifers, attaining this aim post calving BW is of critical importance. Ettema and Santos (2004) conducted an economic analysis of the AFC study that was discussed above. Rearing prices for the medium and high AFC groups were $40.34 and $107.89, respectively, more than that of the low AFC collection. Income for each AFC collection was adjusted for the cost of rearing, assessed feed to increase milk yield, stillbirths, diseases, open days, culling, mortality, labor cost, and the value of milk and calf produced as well as the value of a cow at the end of the 310 day studies. Adjusted income was $119.73 and $9.08 more for the medium and high AFC, respectively, than for the low AFC. These values were not significantly diverse implying no single AFC had an economic benefit over another. Nevertheless, these authors (Ettema and Santos, 2004) did not study the net present value of money in their analysis as St-Pierre (2002) did. If this had been considered, it would presumably shift the economic improvement to the low AFC heifers. Good climatic and weather conditions can be effective factors for reducing the age at first calving and cause to increase the fertility of heifers. However, management methods had a significant effect on this trait in some provinces. The primary benefits of reducing AFC include reducing rearing costs as well as reducing the amount of time in which the heifer is only a capital drain on farm resources. The primary disadvantage of reducing AFC is that it is frequently associated with a reduction in first lactation milk yield. Despite this reduction in first lactation milk yield, production per year of herd life is usually increased by reduced AFC. First lactation may be influenced by AFC, future lactations are definitely not. Furthermore, stay ability and health of cows is not influenced by reduced AFC as long as first calf heifers freshen at an adequate weight.

Domestic animals are invaluable resources to study the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) underlying economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured due to the low density of markers used in QTL mapping studies. The genome wide association study (GWAS) utilizing high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Genetic association tests identify differences in allele frequency between cases and controls. Population stratification can be a problem in association studies, such as case-control studies, where the association found could be due to the underlying structure of the population. In current research, Genome wide association technique (Case-control design) was used to evaluate population stratification. Historical population and genome of 10000 cattle were simulated along 100 generations by Mutation-Drift Equilibrium (MDA) technique. By using historical population, 800 inbred and cross bred cattle with ~50000 SNPs on 30 chromosomes were simulated. Genomic control was performed to survey markers with a low prior probability of association with trait (“null markers”) and to estimate population stratification by Q-Q plot and lambda statistics. Deviation of cases/controls ratios between inbred subpopulations causes increasing lambda and population stratification; as lambda was estimated 0.42, 11.31 and 97.77 in additive genetic model with case/control ratios 1.00, 0.77 and 0.33, respectively and 0.47, 8.21 and 57.40 in co-dominant genetic model. Therefore, the more disparate composition cases/controls the more population stratification. When cases and controls were drawn from different randomly mating breeding populations, allele frequencies were different, but these differences may not be related to disease status or complex trait. This means that the assumption of independence of observations is violated. Often this will lead to an overestimation of the significance of an association but it depends on the way the sample is chosen. Population stratification was surveyed between two random groups of crossbred population (400 cases, 400 controls). There was no population stratification among subpopulations of crossbreds in current research; as lambda was estimated 0.55, 0.66, 0.89, 0.76 and 0.41 in co dominant, dominant, recessive, over dominant, additive genetic models, respectively. The main GWAS problem in inbred cattle is population stratification. When cases and controls are drawn from different inbreeding populations, Population Stratification occurs. Lambda and PS is related to Cases/controls ratio among inbred lines, as more deviation ratio of one, more population stratification. It is suggested to control population stratification inbred cattle should not be used unless exactly equal ratio of cases/controls between inbred subpopulations can be achieved and it is better to use of crossbred cattle for genome wide association studies.

Available genomic data and genome-wide association virtual studies provide the possibility of genetic markers detection known to be associated with complex diseases. Genome Wide Associated Studies (GWAS)، which involve direct testing of genetic polymorphisms in large series of disease cases versus controls، provide a powerful approach to identify lower penetrance alleles that cannot be already detected by genetic linkage studies. By utilizing computer and software systems، it is possible to detect the association of SNPs with diseases without prior knowledge of the function or position. GWAS has been conducted in five of the most common cancer types: breast، prostate، colorectal، lung، and melanoma. GWAS of the breast cancer was performed by simulation of 7 known SNPs on chromosomes 2، 5، 6، 8، 10، 11 and 16 for 10000 women. A simulation study was performed using GWASimulator software and data were analyzed by R software (SNPassoc package). The strongest associations were found for rs2981582 in the FGFR2 gene. SNPs rs889312، rs2180341 and rs3817198 were associated with breast cancer. However، SNPs rs13387042، rs2180341 and rs13281615 on chromosomes 2، 6، and 8 were not associated with the disease، which requires more cases and controls to be stimulated. The results of this research showed that the detection of SNPs associated with the disease was easily possible through employing virtual systems based on real data of Hap Map project using R software.

The objective of this study was to estimate genetic parameters coupled with genetic and phonotypic trends for age at first calving (AFC)، open days (OD) and milk yield (MY) of first lactation in Iranian Holstein cows. Records of reproduction and production for genetic evaluation from 1984 to 2005 for AFC، OD and MY were 71736، 20126 and 20126، respectively. Single and two-variable animal models were used to estimate genetic parameters by restricted maximum likelihood procedures and WOMBAT software. heritability of AFC، OD and MY was estimated 0. 20±0. 02، 0. 04±0. 01، 0. 47±0. 9 respectively. Genetic and phonotypic trends of AFC were negative so that phenotype and breeding value average had decreased from 1984 to 2005. Genetic and phonotypic trends of OD and MY were positive. The genetic and phonotypic correlations between OD and MY were +0. 23 and +0. 07 respectively.

Days dry affects especially on milk production and reproduction. Persistency of high milk production cows increases income over feed cost per cow per day of calving interval. Also a shorter dry period reduces the frequency of diet change and facilitates nutrition management. Effect of length of days dry on productive performance of Holstein cows in Yazd province was studied by 1780 records of dairy herds of Yazd province. Strategy of shortening days dry from 60-d to 40-d increases 8% in income over feed cost per cow per day of calving interval in Yazd province. This result suggests increases in the efficiency of milk production especially in hot and dry areas.